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://degradationproject.com/ ) and NEXGENNa (http://nexgenna.org/ ) projects and participation in regular relevant FI meetings. Applicants should hold (or be about to obtain) a PhD in Chemistry, Materials Science, or a closely
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://degradationproject.com/ ) and NEXGENNa (http://nexgenna.org/ ) projects and participation in regular relevant FI meetings. Applicants should hold (or be about to obtain) a PhD in Chemistry, Materials Science, or a closely
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state physics, chemistry and materials science. Demonstrated mastery of diamond anvil cell preparation and sample loading. Experience in synchrotron X-ray diffraction and Raman spectroscopy measurements
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for medicine use before and during pregnancy. This postholder would work primarily on a recently funded programme of work to develop a novel approach to understanding and communicating the Safety of Medicines in
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. Qualification requirements The selected candidate should have a master’s degree in a related field: e.g., civil engineering , mechanical engineering , computational materials science , or applied mathematics
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computer codes to solve some of the daily research problems and have experience with high performance computing. You should have a PhD in Chemistry, Physics or Materials Science with a proven research track
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for data analysis/scientific computing, and excellent decision-making, problem-solving, planning, and organisational skills. Please direct enquiries about the role to Prof Martin Bureau: (martin.bureau
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for data analysis/scientific computing, and excellent decision-making, problem-solving, planning, and organisational skills. The post is full time and fixed term until 30 June 2028. The closing date
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and